600 customers
Here you find instance definitions and the best known solutions (to our knowledge) for the 600 customer instances of Gehring & Homberger's extended VRPTW benchmark. The version reported here has a hierarchical objective: 1) Minimize number of vehicles 2) Minimize total distance. Distance and time should be calculated with double precision, total distance results are rounded to two decimals. Exact methods typically use a total distance objective and use integral or low precision distance and time calculations. Hence, results are not directly comparable.

Instance definitions (text)

Here is a zip file with the 600 customer instances.

 

Best known results for Gehring & Homberger's 600 customer instances

The instance names in blue are hyperlinks to files with corresponding detailed solutions. They have all been checked by our solution checker. Note that many best known solutions do not have a reference to a peer reviewed publication. For these, important details on the solution algorithm, the computing time, and the experimental platform are probably not available. Further, there is no guarantee that the solutions have been produced without using external information, such as detailed solutions published earlier. We may later introduce two categories: 'properly published' and 'freestyle', the latter with no restrictions.

Instance Vehicles Distance Reference Date            Comment
c1_6_1 60 14095.64 GH 2001  Detailed solution by Q
c1_6_2 56 14163.31 PGDR 17-oct-07 Detailed solution by Q
c1_6_3 56 13777.81 BC4 05-apr-12  
c1_6_4 56 13558.54 Q 30-sep-13  
c1_6_5 60 14085.72 VCGP 31-jul-12  
c1_6_6 59 15847.61 Q 26-jan-17  
c1_6_7 57 15752.95 Q 26-jan-17  
c1_6_8 56 14389.82 Q 07-jul-17  
c1_6_9 56 13693.42 VCGP 31-jul-12  
c1_6_10 56 13637.34 NBD 2009 Detailed solution by VCGP
 
c2_6_1 18 7774.10 MB 16-sep-03  There are questions whether 7774.10 is valid, several authors report 7774.16
c2_6_2 17 8264.91 BC4 05-apr-12  
c2_6_3 17 7520.66 Q 29-jun-17  
c2_6_4 17 6909.58 Q 18-mar-15  
c2_6_5 18 7575.20 BSJ2 20-sep-07 Detailed solution by SCR 
c2_6_6 18 7470.36 MB2 18-jul-12 There are questions whether 7470.36 is valid, several authors report 7471.17  
c2_6_7 18 7512.07 BC4 05-apr-12  
c2_6_8 17 7539.73 Q 08-jul-16  
c2_6_9 17 7921.18 Q 06-jul-17  
c2_6_10 17 7255.69 VCGP 31-jul-12  
 
r1_6_1 59 21131.09 MB 16-sep-03  
r1_6_2 54 18705.00 SCR 17-apr-18  
r1_6_3 54 16956.43 EOE 31-oct-16  
r1_6_4 54 15770.50 SCR 08-may-18  
r1_6_5 54 19443.56 SCR 04-may-18  
r1_6_6 54 17864.59 SCR 08-may-18  
r1_6_7 54 16544.69 SCR 05-apr-18  
r1_6_8 54 15622.78 SCR 12-apr-18  
r1_6_9 54 18637.24 SCR 29-mar-18  
r1_6_10 54 17731.06 SCR 29-mar-18  
 
r2_6_1 11 18206.80 VCGP 31-jul-12  
r2_6_2 11 14779.26 NBD 2009  
r2_6_3 11 11191.01 NBD 2009  
r2_6_4 11 8018.59 Q 14-aug-17  
r2_6_5 11 15096.20 BC4 05-apr-12  
r2_6_6 11 12503.26 NBD 2009  
r2_6_7 11 10066.34 VCGP 31-jul-12  
r2_6_8 11 7572.76 Q 03-jul-17  
r2_6_9 11 13377.56 NBD 2009 Detailed solution by BC4
r2_6_10 11 12253.47 BC4 05-apr-12  
 
rc1_6_1 55 17014.17 SCR 29-sep-17  
rc1_6_2 55 15920.75 Q 23-dec-16  
rc1_6_3 55 15204.64 Q 23-dec-16  
rc1_6_4 55 14777.67 Q 23-dec-16  
rc1_6_5 55 16566.24 Q 23-dec-16  
rc1_6_6 55 16504.25 Q 23-dec-16  
rc1_6_7 55 16077.12 Q 07-sep-17  
rc1_6_8 55 15914.91 Q 23-dec-16  
rc1_6_9 55 15826.24 Q 23-dec-16  
rc1_6_10 55 15675.99 Q 23-dec-16  
 
rc2_6_1
14 13324.93 BC4 05-apr-12  
rc2_6_2 12 11555.51 BC4 05-apr-12  
rc2_6_3 11 9444.99 VCGP 31-jul-12  
rc2_6_4 11 7065.72 Q 15-nov-17  
rc2_6_5 11 13000.84 NBD 2009  
rc2_6_6 11 11933.88 BC4 05-apr-12  
rc2_6_7 11 10724.85 NBD 2009  
rc2_6_8 11 10007.82 NBD 2009  
rc2_6_9 11 9580.87 NBD 2009  
rc2_6_10 11 9069.41 NBD 2009  
    0

References

BC4, Mirosław BŁOCHO, Zbigniew J. CZECH, "A parallel memetic algorithm for the vehicle routing problem with time windows". 3PGCIC 2013, 8th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing.

BSJ2 - Bjørn Sigurd Johansen, BjornSigurdJohansen@hotmail.com, DSolver version2 05-2005

BVH - R. Bent and P. Van Hentenryck, "A Two-Stage Hybrid Local Search for the Vehicle Routing Problem with Time Windows," Technical Report CS-01-06, Department of Computer Science, Brown University, 2001.

EOE - Eirik Krogen Hagen, EOE Koordinering DA. Exploring infeasible and feasible regions of the VRPTW and PDPTW through penalty based tabu search. Working paper.

GH - H. Gehring and J. Homberger, "A Parallel Two-phase Metaheuristic for Routing Problems with Time Windows," Asia-Pacific Journal of Operational Research, 18, 35-47, (2001).

JG - Jakub Grzegorek (2017). Improved Hybrid Genetic Search with Advanced Diversity Control, forthcoming MEng thesis, Imperial College London.

MB - Mester, D. and O. Bräysy (2005), “Active Guided Evolution Strategies for Large Scale Vehicle Routing Problems with Time Windows”. Computers & Operations Research 32, 1593-1614.

MB2 - Mester, D & O. Bräysy (2012). "A new powerful metaheuristic for the VRPTW”, working paper, University of Haifa, Israel.

MK - M. Koch, "An approach combining two methods for the vehicle routing problem with time windows",  The solutions were presented at EURO and EURO XX Conference 2004.

NBC - Jakub Nalepa, Miroslaw Blocho, and Zbigniew J. Czech. "Co-operation schemes for the parallel memetic algorithm". In Roman Wyrzykowski, Jack Dongarra, Konrad Karczewski, and Jerzy Waniewski, editors, Parallel Processing and Applied Mathematics, Lecture Notes in Computer Science, pages 191–201. Springer Berlin Heidelberg, 2014. ISBN 978-3-642-55223-6. doi: 10.1007/978-3-642-55224-3 19.

NBD - Yuichi Nagata, Olli Bräysy, and Wout Dullaert (2010). A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows. Comput. Oper. Res. 37, 4 (April 2010), 724-737.

PGDR - Eric Prescott-Gagnon, Guy Desaulniers and Louis-Martin Rousseau. A Branch-and-Price-Based Large Neighborhood Search Algorithm for the Vehicle Routing Problem with Time Windows. (2007)

Q - Quintiq. http://www.quintiq.com/optimization/vrptw-world-records.html .

RP - S. Ropke & D.Pisinger. "A general heuristic for vehicle routing problems",  technical report, Department of Computer Science, University of Copenhagen.

 

SCR - Piotr Sielski (psielski@emapa.pl), Piotr Cybula, Marek Rogalski, Piotr Beling and Andrzej Jaszkiewicz, Emapa S.A. (http://www.emapa.pl), "New methods of VRP problem optimization", unpublished research funded by The National Centre for Research and Development. project number: POIR.01.01.01.-00-0222/16.

VCGP - T. Vidal, T. G. Crainic, M. Gendreau, C. Prins. "A hybrid genetic algorithm with adaptive diversity management for a large class of vehicle routing problems with time-windows", Computers & Operations Research, Vol. 40, No. 1. (January 2013), pp. 475-489.

Published April 18, 2008